ZVCV: Zero-Variance Control Variates

Stein control variates can be used to improve Monte Carlo estimates of expectations when the derivatives of the log target are available. This package implements a variety of such methods, including zero-variance control variates (ZV-CV, Mira et al. (2013) <doi:10.1007/s11222-012-9344-6>), regularised ZV-CV (South et al., 2018 <doi:10.48550/arXiv.1811.05073>), control functionals (CF, Oates et al. (2017) <doi:10.1111/rssb.12185>) and semi-exact control functionals (SECF, South et al., 2020 <doi:10.48550/arXiv.2002.00033>). ZV-CV is a parametric approach that is exact for (low order) polynomial integrands with Gaussian targets. CF is a non-parametric alternative that offers better than the standard Monte Carlo convergence rates. SECF has both a parametric and a non-parametric component and it offers the advantages of both for an additional computational cost. Functions for applying ZV-CV and CF to two estimators for the normalising constant of the posterior distribution in Bayesian statistics are also supplied in this package. The basic requirements for using the package are a set of samples, derivatives and function evaluations.

Version: 2.1.2
Imports: Rcpp (≥ 0.11.0), glmnet, abind, mvtnorm, stats, Rlinsolve, magrittr, dplyr
LinkingTo: Rcpp, RcppArmadillo, BH
Suggests: partitions, ggplot2, ggthemes
Published: 2022-11-02
DOI: 10.32614/CRAN.package.ZVCV
Author: Leah F. South ORCID iD [aut, cre]
Maintainer: Leah F. South <leah.south at hdr.qut.edu.au>
BugReports: https://github.com/LeahPrice/ZVCV/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: ZVCV results


Reference manual: ZVCV.pdf


Package source: ZVCV_2.1.2.tar.gz
Windows binaries: r-devel: ZVCV_2.1.2.zip, r-release: ZVCV_2.1.2.zip, r-oldrel: ZVCV_2.1.2.zip
macOS binaries: r-release (arm64): ZVCV_2.1.2.tgz, r-oldrel (arm64): ZVCV_2.1.2.tgz, r-release (x86_64): ZVCV_2.1.2.tgz, r-oldrel (x86_64): ZVCV_2.1.2.tgz
Old sources: ZVCV archive


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